Evidence map›Paper›PMID 35013577›Full record

ArticleBritish journal of cancer2022

Development and validation of a circulating microRNA panel for the early detection of breast cancer.

Ruiyang Zou, Sau Yeen Loke, Yew Chung Tang, Heng-Phon Too, Lihan Zhou, Ann S G Lee, Mikael Hartman

Erratum issuedAbstract readValidation Study
In one paragraph

Article in British journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 41 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Ruiyang ZouDepartment of Research and Development, MiRXES Lab, Singapore, Singapore.
Sau Yeen LokeCellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre, Singapore, Singapore.
Yew Chung TangDepartment of Research and Development, MiRXES Lab, Singapore, Singapore.
Heng-Phon TooDepartment of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Lihan ZhouDepartment of Research and Development, MiRXES Lab, Singapore, Singapore. lihan_zhou@mirxes.com.ORCID http://orcid.org/0000-0002-1096-2604
Ann S G LeeCellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre, Singapore, Singapore. dmslsg@nccs.com.sg.ORCID http://orcid.org/0000-0001-9719-9332
Mikael HartmanDepartment of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore.ORCID http://orcid.org/0000-0001-5726-9965

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMammography is widely used for breast cancer screening but suffers from a high false-positive rate. Here, we perform the largest comprehensive, multi-center study to date involving diverse ethnic groups, for the identification of circulating miRNAs for breast cancer screening.

methodsThis study had a discovery phase (n = 289) and two validation phases (n = 374 and n = 379). Quantitative PCR profiling of 324 miRNAs was performed on serum samples from breast cancer (all stages) and healthy subjects to identify miRNA biomarkers. Two-fold cross-validation was used for building and optimising breast cancer-associated miRNA panels. An optimal panel was validated in cohorts with Caucasian and Asian samples. Diagnostic ability was evaluated using area under the curve (AUC) analysis.

resultsThe study identified and validated 30 miRNAs dysregulated in breast cancer. An optimised eight-miRNA panel showed consistent performance in all cohorts and was successfully validated with AUC, accuracy, sensitivity, and specificity of 0.915, 82.3%, 72.2% and 91.5%, respectively. The prediction model detected breast cancer in both Caucasian and Asian populations with AUCs ranging from 0.880 to 0.973, including pre-malignant lesions (stage 0; AUC of 0.831) and early-stage (stages I-II) cancers (AUC of 0.916).

conclusionsOur panel can potentially be used for breast cancer screening, in conjunction with mammography.

Indexed as

Gene Expression ProfilingAdultAgedAged, 80 and overBiomarkers, TumorBreast NeoplasmsCase-Control StudiesCirculating MicroRNAEarly Detection of CancerFemaleHumansMiddle AgedNeoplasm StagingROC CurveBiomarkers, TumorCirculating MicroRNA

Identifiers

PMID35013577
PMCPMC8810862

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.